Mayuko Yoda
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- RNA Research and Splicing
- RNA Interference and Gene Delivery
- RNA modifications and cancer
- Circular RNAs in diseases
- RNA and protein synthesis mechanisms
- Advanced biosensing and bioanalysis techniques
Papers in
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- RNA Research and Splicing 5
- RNA modifications and cancer 3
- Advanced biosensing and bioanalysis techniques 2
- RNA Interference and Gene Delivery 2
- Genomics and Chromatin Dynamics 1
- Viral Infectious Diseases and Gene Expression in Insects 1
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- MicroRNA in disease regulation 3
- Cancer-related molecular mechanisms research 2
- Co-authors
- Yukihide Tomari (6 shared papers)Shintaro Iwasaki (2 shared papers)Yuriko Sakaguchi (2 shared papers)Tsutomu Suzuki (2 shared papers)Tomoko Kawamata (2 shared papers)Susumu Katsuma (1 shared paper)Maki Kobayashi (1 shared paper)Qinghua Liu (1 shared paper)
- Journals
- Molecular Cell (1 paper)Chemical Communications (1 paper)Nature Structural & Molecular Biology (1 paper)Cell Reports (1 paper)EMBO Reports (1 paper)
- Partner nations
- JapanUnited StatesBelgium
In The Last Decade
Mayuko Yoda
8 papers receiving 923 citations
Peers
Comparison fields: 5 of 64
- Cancer Research 484
- Molecular Biology 783
- Aging 14
- Endocrinology 16
- Plant Science 111
Countries citing papers authored by Mayuko Yoda
This map shows the geographic impact of Mayuko Yoda's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mayuko Yoda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayuko Yoda more than expected).
Fields of papers citing papers by Mayuko Yoda
This network shows the impact of papers produced by Mayuko Yoda. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mayuko Yoda. The network helps show where Mayuko Yoda may publish in the future.
Co-authors
The 23 scholars most cited alongside Mayuko Yoda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 371 | |
| 2 | 2009 | 291 | |
| 3 | 2013 | 127 | |
| 4 | 2011 | 46 | |
| 5 | 2017 | 38 | |
| 6 | 2012 | 23 | |
| 7 | 2018 | 16 | |
| 8 | 2010 | 14 |
About Mayuko Yoda
Mayuko Yoda is a scholar working on Molecular Biology, Cancer Research, Infectious Diseases, Organic Chemistry and Endocrinology, having authored 8 papers that have together received 926 indexed citations. Recurring topics across this work include RNA Research and Splicing (5 papers), MicroRNA in disease regulation (3 papers), RNA modifications and cancer (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Cancer-related molecular mechanisms research (2 papers), RNA Interference and Gene Delivery (2 papers), Genomics and Chromatin Dynamics (1 paper) and Viral Infectious Diseases and Gene Expression in Insects (1 paper). The work is most often cited by research in Cancer Research (484 citations), Molecular Biology (783 citations), Aging (14 citations), Endocrinology (16 citations) and Plant Science (111 citations). Mayuko Yoda has collaborated with scholars based in Japan, United States and Belgium. Frequent co-authors include Yukihide Tomari, Shintaro Iwasaki, Yuriko Sakaguchi, Tsutomu Suzuki, Tomoko Kawamata, Susumu Katsuma, Maki Kobayashi, Qinghua Liu, Xuecheng Ye and Zain Paroo. Their work appears in journals such as Molecular Cell, Chemical Communications, Nature Structural & Molecular Biology, Cell Reports and EMBO Reports.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.